The design of electric motors through the use of finite element analysis (FEA) requires a substantial amount of simulation time. For example, to develop an optimized motor design, thousands of design evaluations are required, which in some cases takes more than one month to simulate. Thus, it would be desirable to have a method for designing an electric motor that requires a reduced amount of simulation time.
Furthermore, motor and generator (MAG) systems have been extensively applied in critical service areas, including transportation, medical and military systems, where such electric motors are used for electric propulsion/motoring, energy generation, emergency backup power, and the like. The operation of MAGs in critical energy service areas need to be continuously and reliably monitored and predictably maintained. For example, there have been circumstances, where well-maintained diesel power generators that are used to supply emergency energy to systems used to cool nuclear power plants have failed unexpectedly. Additionally, there are still continuous reports of system failures in the case of extremely high power wind turbine generators and high power electrical systems, which have been deployed. Thus, the monitoring systems of MAGs in such critical service areas have failed to provide a suitably comprehensive service to prevent such disasters. Furthermore, the failure of critical service systems may be catastrophic to the power grid and the public as a whole. Thus, if there were a cyber system that could understand the deterioration and able to predict the remaining operating life of physical MAG systems, then such disastrous failures of emergency systems could be prevented.
Therefore, there is a need for a method of designing and customizing a multiphase electric motor using a design and customization algorithm that utilizes reduced simulation time. Furthermore, there is a need for a method of designing and customizing a multiphase electric motor that utilizes or considers environmental factors, such as regional natural disasters that affect the reliability, humidity that affects the load profile of the motor and external temperature that affects the operational efficiency of the electric motor system. In addition, there is a need for a method that generates a five-phase LPM (lumped parameter model) for a multiphase electric motor, such as a PMa-Syn RM (permanent magnet assisted synchronous reluctance motor).